Shaping virtual machine communication traffic

ABSTRACT

Cloud computing platforms having computer-readable media that perform methods to shape virtual machine communication traffic. The cloud computing platform includes virtual machines and a controller. The controller limits the traffic associated with the virtual machines to enable the virtual machines to achieve desired communication rates, especially when a network servicing the virtual machines is congested. The controller may drop communication messages associated with the virtual machines based on a drop probability evaluated for the virtual machines.

BACKGROUND

Conventionally, cloud computing platforms host software applications inan Internet-accessible virtual environment. The cloud computing platformallows an organization to use datacenters designed and maintained bythird parties. The conventional virtual environment supplies small orlarge organizations with requested hardware resources, softwareapplication resources, network resources, and storage resources. Thevirtual environment also provides application security, applicationreliability, application scalability, and application availability.

The conventional datacenters provide the physical computing resources,physical storage resources, and physical network resources. The physicalresources in the data center are virtualized and exposed to theorganizations as a set of application programming interfaces. Theorganizations do not need to maintain their own hardware resources orsoftware resources, or maintain datacenters that are reliable andscalable.

The organizations may access these physical resources efficientlythrough the virtual environment without knowing the details of thesoftware or the underlying physical hardware. In a conventional cloudcomputing platform, the hardware resources and software resources may beshared by organizations who do not trust each other. To prevent denialof service to any one organization, the conventional cloud platformsprovide procedures that maintain equitable access to the sharedresources. Most of the procedures require a significant amount of stateinformation which increases computational and cost overhead in the cloudcomputing platform.

For instance, the sharing procedures may include leaky bucket, tokenbucket, and fair queuing. The leaky bucket procedure storescommunication messages in a queue and transmits the communicationmessages at a constant rate. When the queue is full, communicationmessages are discarded. The token bucket procedure stores communicationmessage in a queue and transmits the communication at a rate that isbased on the number of tokens associated with the queue. Communicationmessage may be discarded if the communication messages wait in thebucket for a predetermined time. The fair queuing procedure storescommunication message in a queue and transmits the communicationmessages at a rate the is equal or proportional to the rate ofexperienced by other queues for other communication sessions. Theseprocedures provide a mechanism to share resources in the cloud but havehigh CPU overhead because of the need to maintaining queues andassociated state for the queues.

SUMMARY

Embodiments of the invention relate, in one regard, to cloud computingplatforms, computer-readable media, and computer-implemented methodsthat shape virtual machine traffic in a cloud computing platform. Thecloud computing platform includes controllers and virtual machines thatare connected to a communication network. The controllers provide astateless mechanism for shaping communication traffic with minimaloverhead.

The controllers monitor traffic on the communication network. Thecontrollers calculate an average communication rate for virtual machinesconnected to the communication network. In turn, a desired sending ratefor the virtual machines is obtained by the controller. The controllerdetermines a drop probability for the virtual machines based on theaverage communication rate. Communication messages in the network aredropped based on the drop probability for the virtual machines.

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the detaileddescription. This summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used in isolation as an aid in determining the scope of the claimedsubject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a network diagram that illustrates an exemplary cloudcomputing platform in accordance with embodiments of the invention;

FIG. 2 is a block diagram that illustrates a communication system havingexemplary controllers and virtual machines in the exemplary cloudcomputing platform in accordance with embodiment of the invention;

FIG. 3 is a logic diagram that illustrates an exemplary method to managevirtual machine communication traffic in accordance with embodiment ofthe invention; and

FIG. 4 is a logic diagram that illustrates an exemplary method todiscard virtual machine communication traffic in accordance withembodiment of the invention.

DETAILED DESCRIPTION

This patent describes the subject matter for patenting with specificityto meet statutory requirements. However, the description itself is notintended to limit the scope of this patent. Rather, the inventors havecontemplated that the claimed subject matter might also be embodied inother ways, to include different steps or combinations of steps similarto the ones described in this patent, in conjunction with other presentor future technologies. Moreover, although the terms “step” and “block”may be used herein to connote different elements of methods employed,the terms should not be interpreted as implying any particular orderamong or between various steps herein disclosed unless and except whenthe order of individual steps is explicitly described. Further,embodiments are described in detail below with reference to the attacheddrawing figures, which are incorporated in their entirety by referenceherein.

As utilized herein, the term “component” refers to any combination ofhardware, software, and firmware.

The cloud computing platform enables sharing of hardware and softwareresources among virtual machines. In some embodiments, virtual machinetraffic is limited to prevent resource starvation in the cloud computingplatform. The cloud computing platform execute traffic shapingprocedures that limit bandwidth utilized by the virtual machines.Accordingly, the cloud computing platform protects shared resources frommalicious virtual machines that attempt to access excess resources toreduce accessibility by other virtual machines. The cloud computingplatform also protects shared resources from inadvertent use of excessnetwork resources by non-malicious virtual machines.

In some embodiments, the cloud computing platform utilizes a queuelessand stateless mechanism to implement bandwidth limiting for the virtualmachines. This mechanism keeps the overhead for each virtual machinelow. In one embodiment, the communication messages for the virtualmachines are transmission control protocol (TCP) communication messages,i.e., packets.

Bandwidth limiting allows an administrator of the cloud computingplatform to set the bandwidth available to a given virtual machine basedon the relationship with the virtual machine. For instance, a smallvirtual machine may be limited to 100 Mbps and a large virtual machinemay be limited to 1 Gbps. Thus, desired communication rates may be setin service level agreements negotiated with each virtual machine in thecloud computing platform.

As one skilled in the art will appreciate, the cloud computing platformmay include hardware, software, or a combination of hardware andsoftware. The hardware includes processors and memories configured toexecute instructions stored in the memories. In one embodiment, thememories include computer-readable media that store a computer-programproduct having computer-useable instructions for a computer-implementedmethod. Computer-readable media include both volatile and nonvolatilemedia, removable and nonremovable media, and media readable by adatabase, a switch, and various other network devices. Network switches,routers, and related components are conventional in nature, as are meansof communicating with the same. By way of example, and not limitation,computer-readable media comprise computer-storage media andcommunications media. Computer-storage media, or machine-readable media,include media implemented in any method or technology for storinginformation. Examples of stored information include computer-useableinstructions, data structures, program modules, and other datarepresentations. Computer-storage media include, but are not limited to,random access memory (RAM), read only memory (ROM), electricallyerasable programmable read only memory (EEPROM), flash memory or othermemory technology, compact-disc read only memory (CD-ROM), digitalversatile discs (DVD), holographic media or other optical disc storage,magnetic cassettes, magnetic tape, magnetic disk storage, and othermagnetic storage devices. These memory technologies can store datamomentarily, temporarily, or permanently.

In one embodiment, the cloud computing platform includes cloudapplications that are available to client devices. The client devicesaccess the cloud computing platform to execute the cloud applications onone or virtual machines. The cloud applications are implemented usingstorage and processing resources available in the cloud computingplatform.

FIG. 1 is a network diagram that illustrates an exemplary computingsystem 100 in accordance with embodiments of the invention. In anembodiment, the computing system 100 shown in FIG. 1 is merely exemplaryand is not intended to suggest any limitation as to scope orfunctionality. Embodiments of the invention are operable with numerousother configurations. With reference to FIG. 1, the computing system 100includes a cloud computing platform 110, cloud applications 120, andclient devices 130.

The cloud computing platform 110 is configured to execute cloudapplications 120 requested by the client devices 130. The cloudcomputing platform 110 maintains computing devices that provide virtualmachines, which execute the cloud application 120. The cloud computingplatform also includes storage resources that store applications andsystem information. The cloud computing platform 110 connects to theclient devices 130 via a communications network, such as a wirelessnetwork, local area network, wired network, or the Internet.

The cloud applications 120 are available to the client devices 130. Thesoftware executed on the cloud computing platform 110 implements thecloud applications 120. In one embodiment, virtual machines provided bythe cloud computing platform 110 execute the cloud applications 120. Thecloud applications 120 may include, but are not limited to, editingapplications, network management applications, finance applications, orany application requested or developed by the client devices 130. Incertain embodiments, some functionality of the cloud application 120 maybe executed on the client devices 130.

The client devices 130 are utilized by a user to interact with cloudapplications 120 provided by the cloud computing platform 110. Theclient devices 130, in some embodiments, must register with the cloudcomputing platform 110 to access the cloud applications 120. Any clientdevice 130 with an account from the cloud computing platform 110 mayaccess the cloud applications 120 and other resources provided in thecloud computing platform 110. The client devices 130 include, withoutlimitation, personal digital assistants, smart phones, laptops, personalcomputers, gaming systems, set-top boxes, or any other suitable clientcomputing device. The client devices 130 include user and systeminformation storage to store user and system information on the clientdevices 130. The user information may include search histories, cookies,and passwords. The system information may include internet protocoladdresses, cached Web pages, and system utilization. The client devices130 communicate with the cloud computing platform 110 to receive resultsfrom the cloud applications 120.

Accordingly, the computing system 100 is configured with a cloudcomputing platform 110 that provides cloud applications 120 to theclient devices 130. The cloud applications 120 remove the burden ofupdating and managing multiple local client applications on the clientdevices 130.

In certain embodiments, the cloud computing platform providescontrollers that shape virtual machine communication traffic. Thecontrollers provide a counter for each virtual machine. The counters maytrack the average sending rate of traffic. The cloud computing platformmay evaluate an exponentially weighted average sending rate for thevirtual machines. Based on the average sending rate, a drop rate iscomputed by the controller for each virtual machines. Communicationmessages are randomly dropped by the controller based on the computedaverage sending rate. In one embodiment, the drop probability may be setvia policy included in the service level agreement governing the virtualmachine. Alternatively, the drop probability may be triggered on demandby a central policy based on network congestion detected by the cloudcomputing platform.

FIG. 2 is a block diagram that illustrates a communication system 200having exemplary controllers 210 and virtual machines 222 in theexemplary cloud computing platform. The controller 210 is connected to acommunication network. The communication network connects the clouddevices 220, and storage resources 230.

The controller 210 monitors communication traffic on the communicationnetwork associated with virtual machines 222 that execute the cloudapplications. The controller 210 includes a communication interface 212,a discard loop 214, processor 216, and nonce engine 218. In certainembodiments, the controller 210 is configured to shape virtual machinecommunication traffic by discarding a fraction of the outbound trafficbased on send rates detected for the virtual machines. The controller isable to shape traffic without maintaining queues for the virtualmachines or communication sessions. The controller 210 measures asending rate of each virtual machine and selects one or morecommunication messages for discarding at a determined probability.

The communication interface 212 receives the communication messages fromthe cloud devices 220 executing the virtual machines 222. Thecommunication interface also transmits the communication messages to thecloud device 220 executing the virtual machines 222. The communicationinterface 212 may include, but is not limited to, Ethernet, orAsynchronous Transfer Mode (ATM) interfaces. The controller 210 maytransmit a communication message to the cloud device 220 over thecommunication interface 212.

The discard loop 214 is used by the controller 210 to discardcommunication messages. The communication messages may be discarded bysending the message to an interface connected to ground. Thecommunication messages are sent to the discard loop when the controller210 determines that a virtual machine 222 has a drop probability above aspecified threshold.

The processor 216 performs calculations for the controller 210. Thecalculations are used by the controller to determine whether to discardcommunication messages for a virtual machine 222. The calculations mayinclude evaluating an average sending rate, a drop probability, and anonce. Based on these calculations, the processor 216 may set a flag todiscard one or more communication messages for the virtual machine 222.

The processor 216 obtains the current sending rate for the virtualmachines 222 executed by cloud device 220. In another embodiment, theprocessor 216 may calculate the current sending rate each time acommunication message is received from the virtual machines 222 bydividing the size of the communication message by the interval sincelast communication message was received by the controller 210 from thevirtual machine 222. The current sending rate is used to determine adrop probability for the virtual machines 222 when the drop probabilityis not set in a service level agreement for the virtual machine 222. Theservice level agreement is stored in storage resource 230, which isaccessed by the processor 216 to determine whether the drop probabilityis set.

In turn, the processor 216 calculates the average sending rate. In oneembodiment, the average sending rate is an exponential average sendingrate (ASR). The processor may evaluateASR=α*previous_ASR+(1−α)*current_SR, where “α” is set by the cloudcomputing platform, the “previous_ASR” is the ASR previously evaluatedfor the virtual machines, and “current_SR” is the current sending ratedetected for the virtual machines. “α” is a rational number. Theexponential averaging uses less memory that other averaging function. Incertain embodiments, the other averaging functions, e.g. mean sendingrate. may be used.

The desired sending rate for the virtual machines 220 is accessed toevaluate the drop probability. The desired sending rate may be set inthe service level agreement. In other embodiments, an administrator mayset the desired sending rate in real time based on the networkcongestions. In yet another embodiment, the desired sending rate may beautomatically set based on the congestion detected on the network. Thedesired sending rate may be automatically decreased as congestion on thecommunication network increases.

The processor 216 calculates the drop probability (DP). The processorevaluates

${{D\; P} = \frac{\beta*( {{A\; S\; R} - {D\; S\; R}} )}{A\; S\; R}},$

“β” is set by the cloud computing platform. β may be set by anadministrator to reduce or increase the number of communication messagesdiscarded. β ranges between 0 and 1.

The nonce engine 218 is a random number generator. It generates a randomnumber for the processor 216. The nonce engine 218 may also provide theprocessor with the maximum random number. In turn, the processor 216 maygenerate a nonce (η) that is used as a threshold. The processor 216evaluates

${\eta = \frac{Random\_ Number}{{Maximum\_ Random}{\_ Number}}},$

“Random_Number” is the random number generated by the nonce engine 218,and “Maximum_Random_Number” is the maximum random number provided by thenonce engine 218. Both “Random_Number” and “Maximum_Random_Number” arerational numbers.

The processor 216 compares the nonce and drop probability. When the dropprobability is greater than the nonce, the processor 216 may discard thecommunication message.

In some embodiments, the drop probability for a virtual machines 222 maybe set by the service level agreement based on network congestion. Forinstance, when there is no network congestion is detected by thecontroller 210, the service level agreement may indicate that theaverage sending rate should be set to the desired sending rate. Hence,the drop probability is zero. And the virtual machine 222 is allowedunrestricted resource utilization. But when network congestion isdetected by the controller 210, the average sending rate is set to aspecific number, e.g., 50 Mbps, 20 Mbps, depending on the congestionlevel and the number of virtual machines 222 accessing the resources inthe cloud computing platform.

Storage resources 230 store the cloud applications and the service levelagreements for each virtual machine 222. In some embodiments, a virtualmachine 222 may have multiple service level agreements. Each servicelevel agreement may correspond to different cloud applications executedby the virtual machine. The service level agreements may set desiredsending rate for the virtual machines 222, desired sending rates for thecloud applications, and desired sending rates for the cloud device 220.In some embodiments, the service level agreements may also store a dropprobability for the virtual machines 222, drop probability for the cloudapplications, and drop probability for the cloud device 220. The storageresource 230 may transmit service level agreements to the controller 210in response to requests for the desired sending rate or dropprobability.

In one embodiment, the cloud computing platform executes cloudapplications on virtual machines running on cloud devices. The cloudcomputing platform shapes communication traffic for the virtualmachines. The cloud computing platform monitors communications rates forthe virtual machines and discards packets based on the communicationrates. The communication rates may include transmission rates andreception rates.

FIG. 3 is a logic diagram that illustrates an exemplary method to managevirtual machine communication traffic. The method initializes in step310. The cloud computing platform maintains an average communicationrate for the virtual machines in the cloud computing platform, in step320. The cloud computing platform may use an exponential average or meanaverage for the virtual machine. In step 330, the cloud computingplatform calculates a drop probability for the virtual machines as afunction of the average communication rate and a desired communicationrate for the virtual machines. The desired communication rate may beobtained from a storage resource storing service level agreements thatspecify the desired sending rate for the virtual machines.Alternatively, the desired sending rate may be set by an administratorof the cloud computing platform.

The cloud computing platform limits transmission communication messagesor reception communication messages associated with the virtual machinesto achieve the desired communication rates for virtual machines in thecloud computing platform. In one embodiment, the limiting oftransmission communication messages or reception communication messagesis triggered when the cloud computing platform detects congestion on anetwork servicing the virtual machines. In turn, the cloud computingplatform randomly drops a communication message for the virtual machineswhen a drop probability for the virtual machines is greater than a noncegenerated by the cloud computing platform, in step 340. The methodterminates in step 350.

In some embodiments, the cloud computing platform shapes communicationtraffic based on sending rates for the virtual machines executing oncloud devices. The cloud computing platform may drop the communicationmessages to reduce overall network congestion. The cloud computingplatform attempts to maintain an agreed service level for the virtualmachines when deciding to whether to drop the communication message.

FIG. 4 is a logic diagram that illustrates an exemplary method todiscard virtual machine communication traffic. The virtual machinecommunication traffic may be governed by Transmission Control Protocol(TCP). The method initializes in step 410. In step 420, the cloudcomputing platform calculates an exponentially weighted average for thesending rate of a virtual machine. The exponentially weighted averagesending rate (ASR) is evaluated for the virtual machine by the cloudcomputing platform, where ASR=α*previous_ASR+(1−α)*current_SR, “α” isset by the cloud computing platform, the “previous_ASR” is the ASRpreviously evaluated for the virtual machines, and “current_SR” is thecurrent sending rate detected by the cloud computing platform for thevirtual machines.

In step 430, the cloud computing platform identifies the desired sendingrate for the virtual machine. The desired sending rate (DSR) may be setin a service level agreement for the virtual machine. Alternatively, thedesired sending rate may be set by an administrator of the cloudcomputing platform.

The cloud computing platform also evaluates a drop probability for acommunication message sent from the virtual machine, in step 440. Thedrop probability (DP) is evaluated for the virtual machines by the cloudcomputing platform, where

${{D\; P} = \frac{\beta*( {{A\; S\; R} - {D\; S\; R}} )}{A\; S\; R}},$

“β” is set by the cloud computing platform.

In step 450, the cloud computing platform drops a communication messagewhen a nonce generated, by the cloud computing platform, for the virtualmachines is greater than the drop probability. The nonce (η) is randomlygenerated for the virtual machines by the cloud computing platform,where

${\eta = \frac{Random\_ Number}{{Maximum\_ Random}{\_ Number}}},$

“Random_Number” is generated by the cloud computing platform, and“Maximum_Random_Number” is set by the cloud computing platform. In anembodiment, the communication message may be a packet. The methodterminates in step 460.

In summary, the cloud computing platform shapes communication trafficassociated with virtual machines executing on cloud devices. The cloudcomputing platform monitors the communication rates and attempts tomaintain an appropriate rate of communication for each virtual machinein the cloud computing platform. The service level agreements associatedwith the virtual machines are processed by the cloud computing platformto ensure an appropriate level of service is maintained for the virtualmachines.

The foregoing descriptions of the embodiments of the invention areillustrative, and modifications in configuration and implementation arewithin the scope of the current description. For instance, while theembodiments of the invention are generally described with relation toFIGS. 1-4, those descriptions are exemplary. Although the subject matterhas been described in language specific to structural features ormethodological acts, it is understood that the subject matter defined inthe appended claims is not necessarily limited to the specific featuresor acts described above. Rather, the specific features and actsdescribed above are disclosed as example forms of implementing theclaims. The scope of the embodiment of the invention is accordinglyintended to be limited only by the following claims.

1. A computer-implemented method to manage virtual machine communicationtraffic in a cloud computing environment having multiple virtualmachines, the method comprising: maintaining an average communicationrate for the virtual machines in the cloud computing platform; computinga drop probability for the virtual machines as a function of the averagecommunication rate and a desired communication rate for the virtualmachines; and randomly dropping a communication message for the virtualmachines when a drop probability for the virtual machines is greaterthan a nonce generated by the cloud computing platform.
 2. Thecomputer-implemented method of claim 1, further comprising: limitingtransmission communication messages or reception communication messageson the virtual machines to achieve the desired communication rates foreach virtual machine in the cloud computing platform.
 3. Thecomputer-implemented method of claim 2, wherein the limiting oftransmission communication messages or reception communication messagesis triggered when the cloud computing platform detects congestion on anetwork servicing the virtual machines.
 4. The computer-implementedmethod of claim 3, wherein the limiting of the communication rates forthe virtual machines is performed without queues.
 5. Thecomputer-implemented method of claim 1, wherein the averagecommunication rate is an average sending rate.
 6. Thecomputer-implemented method of claim 5, wherein the average sending rate(ASR) is evaluated for the virtual machines by the cloud computingplatform, wherein ASR=α*previous_ASR+(1−α)*current_SR, “α” is set by thecloud computing platform, the “previous_ASR” is the ASR previouslyevaluated for the virtual machines, and “current_SR” is the currentsending rate detected by the cloud computing platform for the virtualmachines.
 7. The computer-implemented method of claim 6, wherein thedesired communication rate is the desired sending rate.
 8. Thecomputer-implemented method of claim 7, wherein the desired sending rate(DSR) is set in communication policies for the virtual machine.
 9. Thecomputer-implemented method of claim 8, wherein the drop probability(DP) is evaluated for the virtual machines by the cloud computingplatform, wherein${{D\; P} = \frac{\beta*( {{A\; S\; R} - {D\; S\; R}} )}{A\; S\; R}},$“β” is set by the cloud computing platform.
 10. The computer-implementedmethod of claim 1, wherein the nonce (η) is randomly generated for thevirtual machines by the cloud computing platform, wherein${\eta = \frac{Random\_ Number}{{Maximum\_ Random}{\_ Number}}},$“Random_Number” is generated by the cloud computing platform; and“Maximum_Random_Number” is set by the cloud computing platform.
 11. Oneor more computer-readable media storing instructions to perform a methodto drop virtual machine communication traffic, the method comprising:calculating an exponentially weighted average for the sending rate of avirtual machine; identifying the desired sending rate for the virtualmachine; evaluating a drop probability for a communication message sentfrom the virtual machine; and dropping a communication message when anonce generated for the virtual machines is greater than the dropprobability.
 12. The computer-readable media of claim 11, wherein thecommunication message is a packet.
 13. The computer-readable media ofclaim 12, wherein the virtual machine communication traffic is governedby a Transmission Control Protocol (TCP).
 14. The computer-readablemedia of claim 11, wherein the exponentially weighted average sendingrate (ASR) is evaluated for the virtual machine by a cloud computingplatform, wherein ASR=α*previous_ASR+(1−α)*current_SR, “α” is set by thecloud computing platform, the “previous_ASR” is the ASR previouslyevaluated for the virtual machines, and “current_SR” is the currentsending rate detected by the cloud computing platform for the virtualmachines.
 15. The computer-readable media of claim 14, wherein thedesired sending rate (DSR) is set in a service level agreement for thevirtual machine.
 16. The computer-readable media of claim 15, whereinthe drop probability (DP) is evaluated for the virtual machines by thecloud computing platform, wherein${{D\; P} = \frac{\beta*( {{A\; S\; R} - {D\; S\; R}} )}{A\; S\; R}},$“β” is set by the cloud computing platform.
 17. The computer-readablemedia of claim 1, wherein the nonce (η) is randomly generated for thevirtual machines by the cloud computing platform, wherein${\eta = \frac{Random\_ Number}{{Maximum\_ Random}{\_ Number}}},$“Random_Number” is generated by the cloud computing platform; and“Maximum_Random_Number” is set by the cloud computing platform.
 18. Acloud computing platform configured to shape communication traffic forvirtual machines, the cloud computing platform comprising: virtualmachines that communicate over a network; and a controller configured todrop communication messages associated with the virtual machines when anonce generated for the virtual machines is greater than the dropprobability.
 19. The cloud computing platform of claim 18, wherein thecontroller evaluates the average sending rate (ASR) for the virtualmachine, wherein ASR=α*previous_ASR+(1−α)*current_SR, “α” is set by thecontroller, the “previous_ASR” is the ASR previously evaluated for thevirtual machines, and “current_SR” is the current sending rate detectedby the controller for the virtual machines, and the controller evaluatesthe drop probability (DP) for the virtual machines, wherein${{D\; P} = \frac{\beta*( {{A\; S\; R} - {D\; S\; R}} )}{A\; S\; R}},$“β” is set by the controller, and desired sending rate (DSR) is set in aservice level agreement for the virtual machine and is used by thecontroller if the network servicing the virtual machine is congested.20. The cloud computing platform of claim 19, wherein the controllerrandomly generates nonce (η), wherein${\eta = \frac{Random\_ Number}{{Maximum\_ Random}{\_ Number}}},$“Random_Number” is generated by the controller; and“Maximum_Random_Number” is set by the controller.